code: def policy(self, obs):
      out = torch.tanh(self.fc1(obs))
      out = torch.tanh(self.fc2(out))
      action_mean = self.fc_policy(out)
  
      action_logstd = self.fc_pi_std.expand_as(action_mean)
      action_std = torch.exp(action_logstd)
      return action_mean, action_std
  
file_path: PARL/benchmark/torch/ppo/mujoco_model.py
imports: import parl
  import torch
  import torch.nn
  import numpy
label_desc: Use image node_id 3 for calling the MujocoModel obj's underlying member method code with example usage: obj.policy(obs) and returns: action_mean,  action_std